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Dimension Reduction for the Design Optimization of Large Scale High Voltage Devices Using Co-Kriging Surrogate Modeling

机译:使用协同克里格代理模型简化大型高压设备设计优化的尺寸缩减

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In high voltage (HV) technology, the electrical field distribution can be improved using different field grading methods. These can be categorized into two groups: 1) capacitive or geometrical field grading and 2) resistive field grading. To obtain the optimized field grading effects, some geometrical or material parameters of the HV devices should be optimized. However, these devices are often nonrotationally symmetric and simulation is computationally very time consuming. In this paper, a multilevel surrogate method using co-Kriging methodology is proposed to optimize such large-scale 3-D HV devices. To compute the electrical field distribution of these HV devices, a finite-element method simulator can be run at different levels of complexity, i.e., by reducing the 3-D model into a 2-D model under certain additional assumptions. The co-Kriging method combines expensive runs of highly complex 3-D simulations with relatively inexpensive dimension reduced 2-D simulations. This approach is shown to allow for a faster optimization of a large-scale nonrotationally symmetric problem, while preserving a sufficiently high level of accuracy.
机译:在高压(HV)技术中,可以使用不同的场分级方法来改善电场分布。这些可以分为两类:1)电容或几何场分级和2)电阻场分级。为了获得最佳的场分级效果,应优化高压设备的某些几何或材料参数。但是,这些设备通常是非旋转对称的,并且仿真在计算上非常耗时。本文提出了一种使用协同克里格方法的多级替代方法来优化此类大型3-D HV器件。为了计算这些HV设备的电场分布,可以在不同的复杂程度下运行有限元方法模拟器,即在某些其他假设下将3-D模型简化为2-D模型。共同克里金法将高度复杂的3D模拟的昂贵运行与相对便宜的降维2D模拟相结合。该方法显示出可以在保持足够高的准确性的同时,更快地优化大型非旋转对称问题。

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